2 edition of **Stochastic analysis of spectral broadening by a free turbulent shear layer** found in the catalog.

Stochastic analysis of spectral broadening by a free turbulent shear layer

Jay C Hardin

- 199 Want to read
- 35 Currently reading

Published
**1981**
by National Aeronautics and Space Administration, Scientific and Technical Information Branch, For sale by the National Technical Information Service] in Washington, D.C, [Springfield, Va
.

Written in English

- Stochastic analysis,
- Sound,
- Acoustical engineering

**Edition Notes**

Statement | Jay C. Hardin and John S. Preisser |

Series | NASA technical paper -- 1816 |

Contributions | Preisser, John S, Langley Research Center, United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch |

The Physical Object | |
---|---|

Pagination | 24 p. : |

Number of Pages | 24 |

ID Numbers | |

Open Library | OL14932874M |

A three-dimensional model for turbulent velocity fluctuations in the atmospheric boundary layer is developed and used to calculate scattering of sound. The model, which is based on von Kármán’s spectrum, incorporates separate contributions from shear- and buoyancy-forced turbulence. New equations are derived from the model that predict the strength and diffraction parameters for . Spectral Analysis of Stationary Stochastic Process Hanxiao Liu [email protected] Febru 1/

From the spectral analysis of the turbulent velocities extracted at points along the shear layer, the Strouhal numbers (St) representing the vortex shedding frequency were found to be St = and St = for the left and right shear layers, respectively. Characteristics of shear layers generated by the blockage in the exterior subchannel. @article{osti_, title = {Spectral analysis of the turbulent mixing of two fluids}, author = {Steinkamp, M J}, abstractNote = {The authors describe a spectral approach to the investigation of fluid instability, generalized turbulence, and the interpenetration of fluids across an interface. The technique also applies to a single fluid with large variations in density.

Abstract. The stochastic estimation method educes structure by approximating an average field in terms of event data that are given. The estimated fields satisfy the continuity equation, and they possess the correct scales of length and/or time. In fact, the turbulent medium is, generally, a non-uniform distribution of matter with stochastic, random, density ρ(x), that moves according to stochastic velocity ﬁeld u(x). Recovering the scaling of statistical descriptors for stochastic density and velocity will allow us to get insight into mechanisms, responsible for turbulent driving.

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Stochastic analysis of spectral broadening by a free turbulent shear layer. Washington, D.C.: National Aeronautics and Space Administration, Scientific and.

Stochastic Analysis of Spectral Broadening by a Free Turbulent Shear Layer Jay C. Hardin and John S. Preisser Lajzgley Reseurrb Cetzter Hamnptov, Virginia National Aeronautics and Space Administration Scientific and Technical Information Branch The effect of the time-varying shear layer between a harmonic acoustic source and an observer on the frequency content of the observed sound is considered.

Experimental data show that the spectral content of the acoustic signal is considerably broadened upon passing through such a shear layer. Theoretical analysis is presented which shows that such spectral broadening is entirely Cited by: 4. Stochastic analysis of spectral broadening by a free turbulent shear layer / By Jay C.

Hardin, John S. Preisser, United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch. and Langley Research Center.

Abstract "May Cover."Langley Research Center."Includes bibliographical of. Stochastic analysis of spectral broadening by a free turbulent shear layer.

data show that the spectral content of the acoustic signal is considerably broadened upon passing through such a shear layer. Theoretical analysis is presented which shows that such spectral broadening is entirely consistent with amplitude modulation of the Author: J.

Hardin and J. Preisser. We consider the scattering of sound by turbulence in a jet shear layer. The turbulent, time-varying inhomogeneities in the flow scatter tonal sound fields in such a way as to give spectral broadeni. The instantaneous turbulent velocity field in a three-dimensional wall jet was estimated from the fluctuating wall pressure using a spectral linear stochastic estimation technique.

The wall jet investigated issued from a long square channel with Reynolds number of 90, A theoretical analysis based on the Born approximation permits the prediction of the spectral broadening fairly well when the parameter Ml/A (where M is the flow Mach number.

the shear layer thickness and A the acoustic wavelength) is smaller than about 1~5. In aeroacoustics, spectral broadening refers to the scattering of tonal sound fields by turbulent shear layers, whereby the interaction of the sound with turbulent flow results in power lost from the tone and distributed into a broadband field around the tone frequency.

By adopting this viewpoint in the framework of triple decomposition of the instantaneous flow into the mean field, coherent motion and small-scale turbulence, a strongly nonlinear dynamical model was constructed to describe the formation and development of coherent structures in incompressible turbulent free shear layers (Wu & Zhuang, J.

Fluid. The first attempts of numerical calculation of the spectral broadening by a jet shear layer have been performed by Ewert et al. 16, 17 and showed promising results in the ability of the method to.

Grabowski and Abade (, hereafter GA17) developed a simple approach to investigate droplet spectral broadening in turbulent clouds through a stochastic condensation mechanism referred to as eddy mechanism, suggested about three decades ago by Cooper (), supposes that droplets arriving at a given location within a turbulent cloud follow different trajectories and that.

This trend may be linked to the well-known spectral broadening due to the propagation through the turbulent shear layer [39]. For the study, it was decided to perform the subsequent beamforming. One-dimensional turbulence, a stochastic simulation of turbulent flow evolution based on application of a mixing-length-type hypothesis to individual turbulent eddies, is used to predict transverse profiles of single-point statistics up to third order for two time-developing planar free shear flows, a mixing layer.

The book consists of two parts followed by a number of appendices. Part I provides a general introduction to turbulent flows, how they behave, how they can be described quantitatively, and the fundamental physical processes involved. Part II is concerned with different approaches for modelling or simulating turbulent flows.

tral analysis reveals that peak spectral energies generally occur at Hz for the streamwise ve- locity component and Hz for the cross-stream and vertical velocity components. Spectra show larger and better defined energy peaks near the shear layer.

Peak spectral energies for suspended sediment concentration occur near 1 Hz throughout the. Spectral analysis of jet turbulence Oliver T. Schmidt1y, Aaron Towne2, Georgios Rigas1, shear layer up to the end of the potential core and that are excited by forcing in the as a result are best understood as statistical objects that emerge from the stochastic turbulent ow.

We use spectral proper orthogonal decomposition (Lumley Select ASYMPTOTIC ANALYSIS OF TURBULENT FREE SHEAR LAYERS. Book chapter Full text access. TURBULENT BOUNDARY LAYER DEVELOPMENT AROUND A ° BEND OF SQUARE CROSS SECTION. mean flow unsteadiness acts to modulate instability fluctuations in amplitude and phase and as a result increases spectral broadening.

Significant nonlinear wave. Contour maps of turbulent flow parameters demonstrate that the flow separation cell and a perturbed shear layer are the main sources of turbulence production and that the distribution of suspended sediment is controlled by spatially dependent macro turbulent flow structures.

Spectral analysis reveals that peak spectral energies generally occur. The examples presented include wakes, jets, shear layers, thermal plumes, atmospheric boundary layers, pipe and channel flow, and boundary layers in pressure gradients.

The spatial structure of turbulent flow has been the subject of analysis in the book up to this point, at which a compact but thorough introduction to statistical methods is given/5(4).

Turbulent mixing and entrainment in a stratified horizontal plane shear layer: joint velocity–temperature analysis of experimental data 10 October | Journal of Fluid Mechanics, Vol. Numerical simulation of acoustic scattering by a plane turbulent shear layer: Spectral broadening .An extension to classical stochastic estimation techniques is presented, following the formulations of Ewing and Citriniti (), whereby spectral based estimation coefficients are derived from the cross spectral relationship between unconditional and conditional events.

This is essential where accurate modeling using conditional estimation techniques are considered.from the highly sheared ﬂow of the turbulent boundary layer, the implications of these results are often novel (F&I). Application of methods of stochastic analysis to the mean velocity proﬁle associated with turbulent shear ﬂow, identiﬁes the statistical properties of the .